论文标题
目标2020挑战呈现现实的散景
AIM 2020 Challenge on Rendering Realistic Bokeh
论文作者
论文摘要
本文回顾了第二个目标现实的散景效果呈现挑战，并提供了拟议的解决方案和结果的描述。参与的团队正在解决现实世界中的散景模拟问题，其目标是使用大规模的退潮来学习一种现实的浅焦点技术！散景数据集由使用佳能7D DSLR摄像机捕获的5K浅 /宽大图像对组成。参与者只能基于一个单一框架来渲染散景效应，而没有其他相机或传感器的任何其他数据。在此挑战中使用的目标度量结合了运行时和用户研究中测得的解决方案的感知质量。为了确保已提交的型号的效率，我们测量了它们在标准桌面CPU上的运行时，并在智能手机GPU上运行了模型。拟议的解决方案大大改善了基线结果，定义了实用的散景效果渲染问题的最新结果。
This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world bokeh simulation problem, where the goal was to learn a realistic shallow focus technique using a large-scale EBB! bokeh dataset consisting of 5K shallow / wide depth-of-field image pairs captured using the Canon 7D DSLR camera. The participants had to render bokeh effect based on only one single frame without any additional data from other cameras or sensors. The target metric used in this challenge combined the runtime and the perceptual quality of the solutions measured in the user study. To ensure the efficiency of the submitted models, we measured their runtime on standard desktop CPUs as well as were running the models on smartphone GPUs. The proposed solutions significantly improved the baseline results, defining the state-of-the-art for practical bokeh effect rendering problem.
